code: def recurrence_matrix(
      data: np.ndarray,
      *,
      k: Optional[int] = ...,
      width: int = ...,
      metric: str = ...,
      sym: bool = ...,
      sparse: Literal[True] = ...,
      mode: str = ...,
      bandwidth: Optional[Union[np.ndarray, _FloatLike_co, str]] = ...,
      self: bool = ...,
      axis: int = ...,
      full: bool = False,
  ) -> scipy.sparse.csc_matrix:
      ...
  
imports: from decorator import decorator
  import numpy
  import scipy
  import scipy.signal
  import scipy.ndimage
  import sklearn
  import sklearn.cluster
  import sklearn.feature_extraction
  import sklearn.neighbors
  from ._cache import cache
  from .None import util
  from .filters import diagonal_filter
  from .util.exceptions import ParameterError
  from typing import Any, Callable, Optional, TypeVar, Union, overload
  from typing_extensions import Literal
  from ._typing import _WindowSpec, _FloatLike_co
label_desc: Use image node_id 4 for calling a global function with example usage: recurrence_matrix(data) without return types